Risk-adjusted outcome measures have been widely advocated for use in nursing home care. Such information may be used in quality improvement efforts, serve as the basis for reimbursements, and help guide consumers in their selection of a nursing home. Pressure ulcer development is an important adverse outcome of nursing home care. Important predictors of pressure ulcer development may now be obtained from databases based on the Minimum Data Set, a comprehensive assessment instrument used in all nursing homes receiving federal funding. We propose to develop a risk-adjustment model that is based on the Minimum Data Set and apply this model to evaluate case-mix adjusted rates of pressure ulcer development at individual nursing homes. We will use an existing database maintained by the National Healthcare (NHC), a private nursing home chain. This database contains information from quarterly Minimum Data Set assessments. Rates of pressure ulcer development will be determined by calculating the fraction of residents without an ulcer on an initial assessment who have a pressure ulcer on a subsequent assessment. Predictors of pressure ulcer development will be identified from among patient characteristics described in the Minimum Data Set. Model performance will be evaluated in a separate validation sample. Observed and expected rates of pressure ulcer development will be calculated for individual nursing homes. We will compare these results to assessments based on other risk adjustment models. We will also apply Bayesian Hierarchical Modeling to the problem of evaluating facility performance. Results from this study could lead to an important management tool for improving nursing home care.